Location tracking devices and other such mobile terminals, e.g. smartphones, typically comprise satellite-based location determination functionality, e.g. a receiver for global positioning system (GPS) or GLONASS (Global Navigation Satellite System) and to some extent cellular communication functionality, e.g. transceiver for collecting cellular data from nearby cells/base stations and reporting it to a receiver at the remote location. To determine a location, a GPS receiver must have current almanac data and ephemeris data for at least three appropriate satellites and the receiver must have an initial estimate of its location. However, the reception of signals from the satellites easily suffers from interruptions caused by landscape obstructions such as geographic features, buildings, trees, etc. Because location tracking devices are often operated in environments, such as cities and urban areas, wherein GPS or generally satellite navigation signal reception will be intermittent, this can result in poor performance of the location tracking system.
WO 2010/055192 discloses a method and system for positioning with enhanced accuracy. The suggested solution yields excellent results based on first collecting, from a number of terminals devices, positioning data such as GPS data and environment data including e.g. cell data during a modelling phase to determine covered area estimates of cell network base stations, whereupon during a positioning phase the mere environment data suffices for accurate positioning due to the available covered area estimates with various supplementary data.
In US 2013/00879039, the solution of '192 is developed further by adding vertical information to the position estimates to obtain true 3d positioning.
Notwithstanding the numerous improvements the '192 and '039 clearly introduce to the prior art, the associated solutions may still be optimized having regard to a number of factors and different possible use scenarios.
Depending on the capabilities of the entity executing at least part of the modelling or positioning calculation and associated data transfer procedures, the load caused by such procedures is, if not excessive having regard to the properties of the concerned device(s), nevertheless never a benefit, when the data transfer and data processing capacities are somehow limited, which is often the case especially with mobile devices. With genuine mobile devices such as smartphones or phablets having no power cords connected thereto most of the time, the above factors are also emphasized by the relatively modest power capacity the contemporary batteries are able to offer. Yet, various calculations upon positioning tend to add to the processing, and therefore indirectly, to the positioning delay.
Yet, as the information available about the environment of an object, such as a mobile phone, to be tracked becomes all the time more versatile due to the emerge of new communications technologies such as 4G/LTE (Long-Term Evolution), also new possibilities may arise to extend the data input space, whereupon concentrating the positioning efforts around any certain type of data source or a related model may not give optimum results during real-time positioning, when a variety of data sources in terms of different network signals, etc. are however available and detectable by the object to be positioned.